Symptom courses during and after psychotherapy: models and

simulations Robert Perčević

June 2007

Treatment Courses

The Random Walk Model

xt= ?

The Random Walk Model

xt=xt-1

x

t

The Random Walk Model

xt=xt-1+c c<0

x

t

The Random Walk Model

xt=xt-1+c+ψ c<0

V(ψ)>0, E(ψ)=0

Random Variable

The Random Walk Model with Measurement Error

xt=xt-1+c+ψ+εt-εt-1 c<0

V(ψ)>0, E(ψ)=0 V(ε)>0, E(ε)=0

Empirical Verification

• Hypothesis:– (a) homogeneous and (b) independent change rates

• Sample:– Specialized psychotherapeutic hospital– 1210 patients– Most common diagnosis: F32, F33, F60, F50– Treatment between 2 and 77 days– Up to 9 assessments per patient– 4149 observations

• Method:– HLM; (xi,t - xi,t-1) / Δt = (β1 + ai) + (β2 + bi)t + ε

Empirical Verification

• Findings:

β1 sd(I) p β2 p AR MA res

GES -0,0201 0,0103 <0,01 -0,0008 <0,01 0,0036 -0,3473 0,0859

KOE -0,0346 0,0011 <0,01 -0,0002 0,3516 -0,0466 -0,2983 0,1036

PSY -0,0185 0,0179 <0,01 -0,0006 <0,01 0,1622 -0,6501 0,0791

SOZ -0,0042 0,0104 <0,01 -0,0007 <0,01 0,1654 -0,6204 0,0886

KOM -0,0070 0,0003 <0,01 -0,0005 <0,01 0,0035 -0,4071 0,0867

ZUF -0,0109 0,0004 <0,01 -0,0006 <0,01 -0,0812 -0,3539 0,1139

SOU -0,0018 0,0002 <0,01 -0,0006 <0,01 -0,0781 -0,3559 0,0820

How to improve Outcomes?

• Increase treatment length

• Increase effectiveness

• Match treatment and patient – Outcome monitoring

• Identify non-reponders• Adapt treatment length to patients needs

How to improve Outcomes?

How to improve Outcomes?

• Increase treatment length

• Increase effectiveness

• Match treatment and patient – Outcome monitoring

• Identify non-reponders• Adapt treatment length to patients needs

How to improve Outcomes?

• Increase treatment length

• Increase effectiveness

• Match treatment and patient – Outcome monitoring

• Identify non-reponders• Adapt treatment length to patients needs

How to improve Outcomes?

• Increase treatment length

• Increase effectiveness

• Match treatment and patient – Outcome monitoring

• Identify non-reponders• Adapt treatment length to patients needs

How to improve Outcomes?

• Increase treatment length

• Increase effectiveness

• Match treatment and patient – Outcome monitoring

• Identify non-reponders• Adapt treatment length to patients needs

1 1.5 2 2.5 3 3.5 4

"Krank"

"Gesund"

Dichotomes Gesundungskriterium

KPD38 GES

Outcome criteria

Simulation: Treatment Length

x(1…n,0)=initial_distress_distirbution

FOR patient = 1 to n

FOR time = 1… max_treatment_time

x(patient,time)=x(patient,time-1)+c+randomvariable

IF x(patient,time)<cutoff

positive(time)=positive(time)+1

ENDIF

ENDFOR

ENDFOR

PLOT(positive, 1… max_treatment_time)

Simulation: Treatment Length

0 10 20 30 40 50 600

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1Entlassungszustand <2.5 mit EM (Grün) und ohne EM (Rot) :

Durchschittliche Dauer der Behandlung

p

Simulation: Treatment Length

0 10 20 30 40 50 600

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1Entlassungszustand <2.5 mit EM (Grün) und ohne EM (Rot) :

Durchschittliche Dauer der Behandlung

p

Dose-Effect / Cost-Effect / Cost-Benefit

Simulation: Treatment Length

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1Entlassungszustand <2.5 mit EM (Grün) und ohne EM (Rot) :

Durchschittliche Dauer der Behandlung

p

Dose-Effect / Cost-Effect / Cost-Benefit

Efficiency: the relation between Effect and Effort

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1Entlassungszustand <2.5 mit EM (Grün) und ohne EM (Rot) :

Durchschittliche Dauer der Behandlung

p

Simulation: Effectiveness

Simulation: Identification of Nonresponders

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Beobachtungsdauer

p

Anteil der Patienten mit c>=0 unter allen Patienten welche nach der gegebenen Beobachtungsdauer keine Besserung zeigen

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1Entlassungszustand <2.5 mit EM (Grün) und ohne EM (Rot) :

Durchschittliche Dauer der Behandlung

p

Simulation: Adapting Length of Treatment

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KPD38 GES

p

Wahrscheinlichkeit das Norm(al)

Different Outcome Criteria & Adapting Length of Treatment

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Empfohlener Entlassungswert

Effizie

nz

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Empfohlener Entlassungswert

max p

"Gesu

nd"

Different Outcome Criteria & Adapting Length of Treatment

Aftertreatment Courses

Stylized Facts

Stylized Facts

r = -0.435

Model

xt=xt-1+εt-εt-1 V(ε)>0, E(ε)=0

Model

xt=xt-1+εt-εt-1 V(ε)>0, E(ε)=0

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How to avoid Relapses?

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How to avoid Relapses?Example

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How to avoid Relapses? Better outcome at primary treatment

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How to avoid Relapses? Low-intensity continuation of primary

treatment

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How to avoid Relapses? Maintanance treatment

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How to avoid Relapses? Outcome Monitoring